Protective effects of neutrophil serine protease inhibition against ischemia–reperfusion injury in lung or heart transplantation
Bibliographic record
Abstract
Transplanted organs are inevitably exposed to ischemia-reperfusion (IR) injury, which is known to cause graft dysfunction. Functional and structural changes that follow IR tissue injury are mediated by neutrophils through the production of oxygen-derived free radicals, as well as from degranulation which entails the release of proteases and other pro-inflammatory mediators. Neutrophil serine proteases (NSPs) are believed to be the principal triggers of post-ischemic reperfusion damage. Extended preservation times for the transplanted donor organ correlate with heightened occurrences of vascular damage and graft dysfunction. Preservation with α1-antitrypsin, an endogenous inhibitor of NSPs, improves primary graft function after lung or heart transplantation. Furthermore, pre-operative pharmacological targeting of NSP activation in the recipient using chemical inhibitors suppresses neutrophilic inflammation in transplanted organs. Hence, effective control of NSPs in the graft and recipient is a promising strategy to prevent IR injury. In this review, we describe the pathological functions of NSPs in IR injury and discuss their pharmacological inhibition to prevent primary graft dysfunction in lung or heart transplantation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".